Bilibili's Index LLM team open-sourced the Index-Translate translation model, covering 150 languages
BIBIBI
AT A GLANCE
Bilibili released the Index-Translate translation model family supporting 150 languages.
Article
Bilibili open-sources the Index-Translate translation model, supporting 150 languages
PANews September 30 reported that, according to a report by IT Home, Bilibili's Index LLM team released the multilingual translation model family Index-Translate, built on Qwen3.5, and 2B/9B/35B-A3B text model weights are now available on Hugging Face and ModelScope. The models cover 150 languages, support translation instructions for terminology and formatting, among other things, and have been extended to scenarios including subtitle dubbing, controllable syllables, and long-document translation.
Bilibili's Index LLM team released the multilingual translation model family Index-Translate.
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Index-Translate is built on Qwen3.5.
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2B、9B and 35B-A3B text model weights are now available on Hugging Face and ModelScope.
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The models cover 150 languages and support translation instructions for terminology, formatting, and more.
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The models have been extended to scenarios including subtitle dubbing, controllable syllables, and long-document translation.
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The original text stated that PANews reported the news based on a report by IT.
AI-assisted interpretation
The following is analysis, separate from reported facts. Verify important claims independently.
This is a multilingual translation model series available for use or research. Model weights refer to the parameter files required to run a model; 2B、9B and 35B-A3B represent different model sizes.
Why it matters to readers
For beginners, this indicates that the model is used not only for ordinary text translation, but also involves subtitle dubbing, syllable control, and long-document translation.
Beginners can focus on the range of languages it supports, the types of translation instructions, and the platforms on which the model weights are available.
Risks and unknowns
The original text did not provide model evaluation results, so the actual translation quality remains unclear.
The original text did not provide an official Bilibili announcement link or independent verification materials.
The original text did not specify the conditions for using the model weights.
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